Abstract
US Census same-sex couple data represent one of the richest and most frequently used data resources for studying the LGBT population. Recently, the Census Bureau conducted an analysis of a serious measurement problem in these data, finding that as many as 40 % of same-sex couples tabulated in Census 2000 and 28 % of those tabulated in Census 2010 were likely misclassified different-sex couples (O’Connell and Feliz, Bureau of the Census, 2011). As a result, the Census Bureau released new state-level “preferred” estimates for the number of same-sex couples in these years, as well as previously unavailable information regarding the error rate of sex misclassification among different-sex married and unmarried couples by state and year. Researchers can use this information to adjust same-sex couple tabulations for geographic areas below the state level. Using these resources, this study: (1) considers in greater detail how the properties of the same-sex couple error might affect statistical inference, (2) offers a method for developing sub-state estimates of same-sex couples, and (3) demonstrates how using adjusted estimates can improve inference in analyses that rely on understanding the distribution of same-sex couples. In order to accomplish the third task, we replicate an analysis by McVeigh and Diaz (American Sociological Review 74: 891–915, 2009) that used county level Census 2000 unadjusted same-sex couple data, substitute our adjusted same-sex couple estimate, and examine the way in which this substitution affects findings. Our results demonstrate the improved accuracy of the adjusted measure and provide the formula that researchers can use to adjust the same-sex couple distribution in future analyses.
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Notes
For additional information on the same-sex couple data provided by the Census, please see http://www.census.gov/hhes/samesex/data/decennial.html.
This study focuses on making adjustments to counts of same-sex couples. There has also been scholarship that considers how to address the measurement issue when using Census Bureau Public Use Microdata Samples (e.g., Gates and Steinberger 2009). The issue of adjusting for the measurement error within microdata is quite complex and, while certainly very important, is beyond the scope of these analyses.
In 2010, the variation of the error considers a third factor: whether a household used a mail-in response or the non-response form that was generally completed by an enumerator. O’Connell and Feliz (2011) document substantially higher error in the non-response survey format among both married and unmarried different-sex couples along with variation across states. The error for married different-sex couples that used a mail-in form ranged from 0.18 % in Idaho to 0.31 % in the District of Columbia. For married couples who used the non-response form, the error ranged from 0.8 % in Utah to 1.27 % in West Virginia. For unmarried couples, the range was from 0.23 % in Iowa to 0.44 % in DC for mail-in surveys and from 0.81 % in Hawaii to 1.5 % in West Virginia. Unfortunately, the Census Bureau analyses do not explore possible demographic correlates of the error, but they certainly demonstrate substantial variation associated with geography, couple type, and survey format. The Williams Institute (Gates and Cooke 2011) describes a detailed procedure for adjusting sub-state same-sex couple tabulations in Census 2010 that accounts for variation in form type.
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Acknowledgments
We would like to thank Rory McVeigh and Maria-Elena D. Diaz for generously sharing their data for this analysis.
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DiBennardo, R., Gates, G.J. Research Note: US Census Same-Sex Couple Data: Adjustments to Reduce Measurement Error and Empirical Implications. Popul Res Policy Rev 33, 603–614 (2014). https://doi.org/10.1007/s11113-013-9289-2
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DOI: https://doi.org/10.1007/s11113-013-9289-2